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fix: prevent P2 from owning Qdrant lifecycle

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This commit is contained in:
marcopan
2026-08-11 07:00:05 +02:00
parent f5e76fff53
commit e7ac22f0dc
5 changed files with 179 additions and 5 deletions
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harness/tests/test_qdrant_vector_store.py
+84 -2
View File
@@ -33,6 +33,7 @@ class FakeQdrantHttp:
self.distance = distance
self.collection = None
self.payload_indexes: set[str] = set()
self.payload_index_types: dict[str, str] = {}
self.points: dict[str, dict] = {}
self.calls: list[tuple[str, str, dict | None]] = []
self.fail_request: Exception | None = None
@@ -59,7 +60,7 @@ class FakeQdrantHttp:
}
},
"payload_schema": {
field: {"data_type": "keyword"} for field in sorted(self.payload_indexes)
field: {"data_type": self.payload_index_types.get(field, "keyword")} for field in sorted(self.payload_indexes)
},
}
})
@@ -75,6 +76,8 @@ class FakeQdrantHttp:
return FakeResponse(200, {"status": "ok"})
if method == "PUT" and path == "/collections/workspace-semantic/points":
if self.collection is None:
return FakeResponse(404, {"status": "error"})
for point in json["points"]:
self.points[point["id"]] = point
return FakeResponse(200, {"result": {"status": "acknowledged"}})
@@ -161,13 +164,14 @@ def _write_record(record_id: str, kind: str, *, metadata=None):
)
def _store(fake: FakeQdrantHttp) -> QdrantVectorStore:
def _store(fake: FakeQdrantHttp, *, collection_lifecycle="create_if_missing") -> QdrantVectorStore:
return QdrantVectorStore(
base_url="http://qdrant:6333",
collection="workspace-semantic",
workspace_id="demo",
workspace_revision="a" * 40,
expected_dimension=1024,
collection_lifecycle=collection_lifecycle,
request=fake.request,
)
@@ -178,6 +182,84 @@ def test_point_id_is_deterministic_uuidv5():
)
def test_require_existing_refuses_missing_collection_without_mutations():
fake = FakeQdrantHttp()
store = _store(fake, collection_lifecycle="require_existing")
with pytest.raises(VectorStoreError, match="semantic_index_incompatible"):
store.upsert("memory", [_write_record("memory:1", "memory")])
assert [call for call in fake.calls if call[0] == "PUT"] == []
@pytest.mark.parametrize(
("dimension", "distance", "indexes", "index_types"),
[(384, "Cosine", set(), {}),
(1024, "Dot", set(), {}),
(1024, "Cosine", {"content_hash"}, {}),
(1024, "Cosine", {
"content_hash", "document_id", "kind", "record_key", "record_kind",
"vector_generation", "workspace_id", "workspace_revision",
}, {"kind": "integer"})],
)
def test_require_existing_refuses_incompatible_collection_without_mutations(
dimension, distance, indexes, index_types
):
fake = FakeQdrantHttp(dimension=dimension, distance=distance)
fake.collection = {"vectors": {"size": dimension, "distance": distance}}
fake.payload_indexes = indexes
fake.payload_index_types = index_types
store = _store(fake, collection_lifecycle="require_existing")
with pytest.raises(VectorStoreError, match="semantic_index_incompatible"):
store.upsert("memory", [_write_record("memory:1", "memory")])
assert [call for call in fake.calls if call[0] == "PUT"] == []
def test_require_existing_writes_compatible_collection_without_lifecycle_mutations():
fake = FakeQdrantHttp()
fake.collection = {"vectors": {"size": 1024, "distance": "Cosine"}}
fake.payload_indexes = {
"content_hash", "document_id", "kind", "record_key", "record_kind",
"vector_generation", "workspace_id", "workspace_revision",
}
store = _store(fake, collection_lifecycle="require_existing")
assert store.upsert("memory", [_write_record("memory:1", "memory")]) == 1
assert not [call for call in fake.calls if call[0] == "PUT" and call[1].endswith("/index")]
def test_require_existing_write_fails_after_collection_is_deleted_without_recreating():
fake = FakeQdrantHttp()
fake.collection = {"vectors": {"size": 1024, "distance": "Cosine"}}
fake.payload_indexes = {
"content_hash", "document_id", "kind", "record_key", "record_kind",
"vector_generation", "workspace_id", "workspace_revision",
}
original_request = fake.request
deleted = False
def request(method, url, **kwargs):
nonlocal deleted
response = original_request(method, url, **kwargs)
if method == "GET" and url.endswith("/collections/workspace-semantic") and not deleted:
deleted = True
fake.collection = None
return response
store = QdrantVectorStore(
base_url="http://qdrant:6333", collection="workspace-semantic", workspace_id="demo",
workspace_revision="a" * 40, expected_dimension=1024,
collection_lifecycle="require_existing", request=request,
)
with pytest.raises(VectorStoreError):
store.upsert("memory", [_write_record("memory:1", "memory")])
assert not [call for call in fake.calls if call[0] == "PUT" and call[1].endswith("/collections/workspace-semantic")]
def test_upsert_creates_collection_and_keyword_indexes_idempotently():
fake = FakeQdrantHttp()
store = _store(fake)
harness/tests/test_registry_evidence_config.py
+57
View File
@@ -10,6 +10,7 @@ from tht.adapters.evidence import HttpManifestEvidenceSource
from tht.adapters.factory import build_evidence_sources
from tht.cli import app
from tht.config import ConfigError, load_config
from tht.jobs.dwh_pipeline import config_dwh_binding
SIGNED_CANARY = "SIGNED-CANARY-QUERY"
ACCESS_CANARY = "ACCESS-CANARY"
@@ -350,3 +351,59 @@ def test_validation_repr_cli_and_exception_output_never_disclose_transport_secre
assert result.exit_code == 0
assert_no_canaries(result.stdout)
assert_no_canaries(result.stderr)
def _qdrant_config_yaml(tmp_path, *, registry: bool) -> dict:
value = {
"dwh": {
"type": "postgres_direct",
"connection": {
"database": "analytics", "schema": "public", "user": "reader",
"password": "not-a-canary",
},
},
"vectors": {
"type": "qdrant", "base_url": "http://localhost:6333",
"collection": "workspace-semantic",
},
"embeddings": {
"base_url": "http://localhost:11434", "model": "qwen3-embedding:0.6b", "dim": 1024,
},
"evidence": {"source_root": str(tmp_path / "evidence")},
}
if registry:
value["runtime_identity"] = {
"workspace_id": "demo-workspace", "workspace_revision": "a" * 40,
}
return value
@pytest.mark.parametrize("mode", ["session", "maintenance"])
def test_registry_runtime_configs_require_existing_qdrant_collection(tmp_path, mode):
path = tmp_path / f"{mode}.yaml"
path.write_text(yaml.safe_dump(_qdrant_config_yaml(tmp_path, registry=True)))
cfg = load_config(path)
assert cfg.vectors.collection_lifecycle == "require_existing"
def test_legacy_runtime_config_keeps_create_capable_qdrant_default(tmp_path):
path = tmp_path / "legacy.yaml"
path.write_text(yaml.safe_dump(_qdrant_config_yaml(tmp_path, registry=False)))
cfg = load_config(path)
assert cfg.vectors.collection_lifecycle == "create_if_missing"
def test_registry_session_and_maintenance_bindings_are_equal(tmp_path):
values = _qdrant_config_yaml(tmp_path, registry=True)
session_path = tmp_path / "session.yaml"
maintenance_path = tmp_path / "maintenance.yaml"
session_path.write_text(yaml.safe_dump(values))
maintenance_path.write_text(yaml.safe_dump(values))
assert config_dwh_binding(load_config(session_path)) == config_dwh_binding(
load_config(maintenance_path)
)
harness/tht/adapters/factory.py
+1
View File
@@ -38,6 +38,7 @@ def build_vector_store(cfg: Config, *, require_write: bool = False) -> VectorSto
workspace_id=cfg._workspace_id,
workspace_revision=cfg._workspace_revision,
expected_dimension=cfg.embeddings.dim if cfg.embeddings is not None else None,
collection_lifecycle=resource.collection_lifecycle,
)
case other: # pragma: no cover - Pydantic's discriminator rejects this first.
raise ConfigError(f"Adapter vector non supportato: {other}")
harness/tht/adapters/vector/qdrant.py
+14 -2
View File
@@ -55,6 +55,7 @@ class QdrantVectorStore:
workspace_id: str,
workspace_revision: str | None = None,
expected_dimension: int | None = None,
collection_lifecycle: str = "create_if_missing",
request: Callable[..., object] | None = None,
connect_timeout: float = 2.0,
read_timeout: float = 10.0,
@@ -64,6 +65,9 @@ class QdrantVectorStore:
self._workspace_id = workspace_id
self._workspace_revision = workspace_revision
self._expected_dimension = expected_dimension
if collection_lifecycle not in ("create_if_missing", "require_existing"):
raise ValueError("Unsupported Qdrant collection lifecycle")
self._collection_lifecycle = collection_lifecycle
self._request = request or requests.request
self._timeout = (connect_timeout, read_timeout)
@@ -306,6 +310,8 @@ class QdrantVectorStore:
if response is None:
if not strict:
raise VectorStoreError("Qdrant collection is missing")
if self._collection_lifecycle == "require_existing":
raise VectorStoreError("Qdrant collection configuration mismatch (semantic_index_incompatible)")
self._call(
"PUT",
f"/collections/{self._collection}",
@@ -328,11 +334,17 @@ class QdrantVectorStore:
self._expected_dimension is not None
and (size != self._expected_dimension or distance != "Cosine")
):
raise VectorStoreError("Qdrant collection configuration mismatch")
raise VectorStoreError("Qdrant collection configuration mismatch (semantic_index_incompatible)")
payload_schema = result.get("payload_schema")
if not isinstance(payload_schema, dict):
raise VectorStoreError("Qdrant returned malformed collection response")
for field_name in _KEYWORD_INDEXES:
if field_name not in result.get("payload_schema", {}):
field = payload_schema.get(field_name)
if not isinstance(field, dict) or field.get("data_type") != "keyword":
if not strict:
raise VectorStoreError("Qdrant collection payload indexes mismatch")
if self._collection_lifecycle == "require_existing":
raise VectorStoreError("Qdrant collection configuration mismatch (semantic_index_incompatible)")
self._call(
"PUT",
f"/collections/{self._collection}/index",
harness/tht/config.py
+23 -1
View File
@@ -222,6 +222,9 @@ class QdrantConfig(BaseModel):
type: Literal["qdrant"]
base_url: str
collection: str = Field(min_length=1)
# Internal runtime policy. Registry-rendered configs must not create or alter
# the workspace-owned semantic collection; legacy configs retain compatibility.
collection_lifecycle: Literal["create_if_missing", "require_existing"] = "create_if_missing"
VectorResourceConfig = Annotated[
@@ -547,6 +550,25 @@ def load_config(path: Path) -> Config:
_validate_internal_embedding_contract(expanded, path)
_validate_internal_vector_contract(expanded, path)
translated, used_legacy = translate_legacy_config(expanded)
vectors = translated.get("vectors")
resource_vector = expanded.get("resources", {}).get("vector") if isinstance(
expanded.get("resources"), dict
) else None
if (
isinstance(vectors, dict)
and vectors.get("type") == "qdrant"
and isinstance(resource_vector, dict)
and "collection_lifecycle" in resource_vector
):
vectors["collection_lifecycle"] = resource_vector["collection_lifecycle"]
# runtime_identity is the registry marker. The lifecycle is an internal
# runtime policy, never a descriptor-controlled option.
if (
isinstance(translated.get("runtime_identity"), dict)
and isinstance(vectors, dict)
and vectors.get("type") == "qdrant"
):
vectors["collection_lifecycle"] = "require_existing"
_populate_legacy_views(translated)
try:
cfg = Config.model_validate(translated)
@@ -662,7 +684,7 @@ def _validate_internal_vector_contract(raw: dict[str, Any], path: Path) -> None:
engine = vector.get("engine")
base_url = vector.get("base_url")
collection = vector.get("collection")
allowed = {"engine", "base_url", "collection"}
allowed = {"engine", "base_url", "collection", "collection_lifecycle"}
unexpected = sorted(set(vector) - allowed)
if unexpected:
raise ConfigError(